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Using Network Reliability to Understand International Food Trade Dynamics

机译:利用网络可靠性了解国际食品贸易动态

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Understanding the structural and dynamical properties of food networks is critical for food security and social welfare. Here, we analyze international trade networks corresponding to four solanaceous crops obtained using the Food and Agricultural Organization trade database using Moore-Shannon network reliability. We present a novel approach to identify important dynamics-induced clusters of highly-connected nodes in a directed weighted network. Our analysis shows that the structure and dynamics can greatly vary across commodities. However, a consistent pattern that we observe in these commodity-specific networks is that almost all clusters that are formed are between adjacent countries in regions where liberal bilateral trade relations exist. Our analysis of networks of different years shows that intensification of trade has led to increased size of clusters, which implies that the number of countries spared from the network effects of disruption is reducing. Finally, applying this method to the aggregate network obtained by combining the four networks reveals clusters very different from those found in the constituent networks.
机译:了解粮食网络的结构和动态特性对于粮食安全和社会福利至关重要。在这里,我们使用Moore-Shannon网络可靠性分析与使用粮食及农业组织贸易数据库获得的四种茄科作物相对应的国际贸易网络。我们提出了一种新颖的方法来确定定向加权网络中重要的动力学诱导的高度连接的节点的群集。我们的分析表明,不同商品的结构和动态变化很大。但是,我们在这些特定于商品的网络中观察到的一个一致模式是,几乎所有形成的集群都在存在自由双边贸易关系的区域中的相邻国家之间。我们对不同年份网络的分析表明,贸易的加强导致集群规模的增加,这意味着不受网络干扰影响的国家数量正在减少。最后,将此方法应用于通过组合四个网络而获得的聚合网络,可以发现与组成网络中发现的集群非常不同的集群。

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